In this investigation, I wanted to observe some trends, and relationships from the Ford Gobike trip data. My main focus was to find out when most trips are taken in terms of the time of the day, whether morning, afternoon or night time. I also wanted to find out how long the average trip takes. Furthermore, focus on the relationships and distributions of the features of interest which were the duration_sec, member_gender, member_birth_year and start_time variables and find out some interesting insights that may help in coming up with some better marketing strategies to target the users.
The Ford GoBike Trip data is the selected dataset being investigated in this project. It includes information about the rides made in a bike-sharing system covering the greater San-Francisco Bay area. The dataset contains trip data for the month of February 2019 and consists of 183,412 trips with 16 features.
This dataset contains the object, int64 and float64 datatypes. Upon carrying a bit of data wrangling steps, we found some issues to do with inappropriate data types and missing values. This issues were fixed before any exploration was undertaken.
Market St at 10th St
San Francisco Caltrain Station 2 (Townsend St at 4th St)
Berry St at 4th St
Montgomery St BART Station (Market St at 2nd St)
Powell St BART Station (Market St at 4th St)
The market area is one of the best start station location as it in the center of the business district.
The subscriber is the most prominent user type.
On average, most trips do not last for more than 60 minutes.
The afternoon and morning periods of the day are the peak periods when most trips are taken.
Relationship between Periods of the day and user type.
For both user types, the male gender are in majority.